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lewis and charlie, 
loves of my life 


Many people helped to insure the successful completion 
of this study. I thank Pat Miller for guiding me through the 
intense graduate school learning process. Pat involved me in 
her research early in my graduate school career, and her 
enthusiasm for research was contagious! Pat always makes 
time when her students need assistance and is a very 
dedicated professional. Pat also showed all of us that a 
woman can have a serious career and a family simultaneously. 
She not only was my adviser but a terrific friend as well. 

I would like to thank two members of my committee, Scott 
Miller and James Algina, who taught me about research design 
and statistics, both in and out of the classroom. Both were 
excellent teachers and assisted me with numerous questions 
throughout my graduate school career. I also thank the other 
members of my committee, Ira Fischler, Rich Griggs, and Robin 
West, for their support. 

I am grateful to Peggy Blitch and the teachers and 
students at Martha Manson Academy for giving me and my 
assistants a warm welcome at the school. I also appreciate 
the numerous occasions that Ruth Duncan and the teachers and 
students at P.K. Yonge Laboratory School did the same. 


Two fellow graduate students rescued me from doom, when 
I thought making the videotapes would be impossible. Al 
Avendano had the "know-how" to film and produce them. Pat 
Aloise narrated them, because I lost my voice on the day the 
camera was set to roll! The cooperation among graduate 
students truly makes the program at the University of Florida 

I was fortunate to have the assistance of several very 
dedicated undergraduate assistants, who contributed many 
hours of their time and talents to help make this study 
possible. Carol Lewald and Rick Anderson helped to test 
subjects for the study. Kathleen G. Cossey and Carol Lewald 
coded and scored (and scored and coded!) the data. Others 
who assisted with various aspects of the study were Randi 
Clement, Troy Zarcone, Jackie Spiegel, Spencer White, Nikarre 
Redcoff, and Coreen E. Prochnow at the University of Florida; 
Lisa Mallet, Jean Muransky, Rose Kramer, Gary Kolvachik, Beth 
Owen, and Teri Miller at Muskingum College; and Erica Miller, 
a Sarah Lawrence student-to-be. 

Cecil Chapman typed the labels for the birds on, what 
was then, her brand-new laser printer. Cecil helps everyone, 
and her cheerfulness makes the developmental/cognition area a 
brighter place to be. 

Bill Hardy was the much-depended-upon ornithologist who 
helped with the original lists of birds, loaned me slides for 
the videotapes, and answered, what seemed to be, my 10 


million questions about birds. I knew nothing about birds 
when I began this project! 

I thank Larry Normansell, my colleague at Muskingum 
College, for his assistance in producing a poster version of 
this paper. The poster for the Conference on Human 
Development in Charleston was aesthetically pleasing! 

I thank David Bjorklund for keeping me informed of his 
research and sending me a computer program for defining which 
children were "strategic." I became excited about conducting 
memory development research after attending a symposium at 
the Conference on Human Development in Nashville (1985) 
during which David, Peter Ornstein, and others debated the 
nature of strategies. 

I especially thank Lewis for enabling me to pursue a 
career. In addition to his generous donation of time 
assisting with computer questions and problems, Lewis is 
always helping behind the scenes . I appreciate all that he 
does . 

Thanks to my wonderful graduate school friends of the 
past: Gillian, Marite, Malia, Vern, John, Terry, Nan, and 
Carol for providing "kinship." The spirit and warmth of 
Florida live on in all of us (though most of us have migrated 
north) . Now as another clan of graduate students makes their 
way up the graduate school rungs, may they keep the spirit of 
Florida alive: Pat, Maggie, Janet, Nanci, Bob, Al, Wendy, 
and others. Until we meet again, see you at SRCD! 







The Beginning of Research Related 

to Memory 1 

Review of the Literature Investigating 

the Answer to "What is Memory the 

Development of? 2 

Strategy Use Develops 3 

Knowledge Develops 8 

Current Debates in the Field of Memory 

Development 11 

The Definition and Measurement of 

Knowledge 14 

Purpose of this Study 19 

Hypotheses 24 


Subj ects 25 

Materials 26 

Design 29 

Procedure 31 

Memory Test 3 2 

Knowledge Tests 3 3 

Coding and Scoring 36 

Memory Test 3 6 

Knowledge Tests 37 

Clustering 39 

Overt Study Strategies 39 



Did Knowledge Change? 42 

Within-Subj ect Analyses 42 

Between-Subject Analyses 49 

Did Recall, Clustering, and Strategy Use 

Change? 52 

Within-Subj ect Analyses 52 

Between-Subj ect Analyses 54 

Individual-Subject Analysis of Changes in 

Knowledge and Memory 56 

Were There Significant Correlations Among 
Knowledge, Clustering, Strategy Use, 
and Memo r y ? 5 8 


Summary of the Results 6 2 

Why Correlation But Not Causality? 66 

Other Issues and Future Research 74 


















Table page 

2-1 Testing Sequence for Three Groups of Children 
Tested for their Recall and/or Knowledge of 
Birds 30 

3-1 Pre-VIDEO and Post-VIDEO Means (and Standard 

Deviations) for Each Knowledge Test 42 

3-2 Means (and Standard Deviations) of Pretest 

and Posttest Recall for Males and Females 

in the Memory Test Twice Group 5 3 

3-3 Means (and Standard Deviations) of Pre-VIDEO 
and Post-VIDEO Clustering and Recall for 
Younger and Older Children 55 

3-4 Individual-Subject Analysis for Patterns of 
Changes on the Knowledge and Memory Tests 
by Age 57 

3-5 Post-VIDEO Correlations Between Knowledge, 

Clustering, or Strategy Use and Recall for 
Groups of Children 59 

3-6 Correlations Among the Knowledge Tests 

by Age 60 


Abstract of Dissertation Presented to the Graduate School 
of the University of Florida in Partial Fulfillment of the 
Requirements for the Degree of Doctor of Philosophy 



Darlene DeMarie-Dreblow 

December 19 88 

Chairperson: Patricia H. Miller 
Major Department: Psychology 

Previous research on memory development suggests that 
increases in knowledge during development may encourage 
strategy use and improve recall. Unlike these correlational 
studies, the present study tested this hypothesis by 
experimentally manipulating knowledge. 

Knowledge about birds among 44 younger (mean age: 8-7) 
and 53 older (mean age: 10-5) children was assessed via four 
tests. 1) GROUPING: Children placed 45 picture/name cards of 
birds into groups that they thought belonged together, and 
titled each group. The number of birds placed into meaning- 
based groups (e.g., pet birds) was tallied. 2) LISTING: 
Children said all the members they knew for six experimenter- 
designated categories (e.g., birds of prey, songbirds). 3) 
FACTS: Children stated all the facts they knew about each of 


the birds. 4) MATCHING: Children placed the birds into the 
six possible categories used for LISTING. 

Children's strategies while studying 20 picture/name 
cards of birds were videotaped, coded, and scored. Depending 
upon their assigned groups, children took either the four 
knowledge tests or a memory test both before and after, or 
they took all tests only after viewing five videotapes about 
birds. The videotapes, shown in the classroom by the regular 
classroom teacher, taught information about the birds and 
emphasized intra-group associations. 

Between-subject analyses showed significantly higher 
knowledge scores after the videotapes than before for both 
sexes on MATCHING, and for boys only on GROUPING. Within- 
subject analyses revealed significant improvements on 
MATCHING, LISTING, and GROUPING. All analyses showed 
substantial increases in the percentage of facts referring to 
general, categorical information. 

Despite significant increases in knowledge and 
significant correlations between knowledge and memory, there 
were not significant improvements in clustering and overt 
study strategies (e.g., rehearsal). Although knowledge 
changes were greater overall for males, only the females in 
the within-subject analysis showed significant improvement in 
recall. Males' recall decreased significantly. The between- 
subject analysis showed no improvement in recall for any 

Either knowledge is not the cause of improvements in 
memory with age, or knowledge is necessary as a first step, 
but not sufficient. Possible reasons for correlation but not 
causality are discussed. 



The Beginning of Research Related to Memory 
The study of memory is a topic that has intrigued 
psychologists for more than 75 years. One of the earliest, 
and most famous, studies of memory was conducted by Hermann 
Ebbinghaus, a German psychologist. Ebbinghaus invented the 
nonsense syllable and used himself as a subject. His measure 
of memory was that of relearning, the time it took to relearn 
a list of nonsense syllables to perfection, after various 
intervals of time (Ebbinghaus, 1913). 

Although other studies appeared during the first 60 
years of the 20th century, that period has been described as 
a "long period of misdirection, confusion, and sterility" 
(Olson, 1983). However, the study of memory blossomed in the 
late 60s, and new methodology facilitated its study. 
Introspection, which was dominant in this country during 
Ebbinghaus' time, was no longer considered a scientific 
method. The information processing approach has prevailed 
since the 1960s. 

Research related to the development of memory 
flourished following a landmark symposium, organized by John 

Flavell, which took place at the biennial meeting of the 
Society for Research in Child Development (SRCD). The title 
of this 1971 symposium was "What is memory the development 
of?" At the 1981 SRCD symposium which marked the ten-year 
anniversary of Flavell ' s symposium, Trabasso (1983) remarked 
that the answer to the general question "What is memory the 
development of?" depends on one's answer to "What is memory?" 
Our conceptions of what memory is have changed since 1971, 
and so have our conceptions of what is developing, but no one 
to date has been able to answer Flavell' s challenging 
question with certainty. 

Review of the Literature Investigating the Answer to: 
"What Is Memory the Development of?" 

Over the past 20 years, several answers to the question 

"What is memory the development of?" have appeared in the 

literature. One answer was that capacity developed (Pascual- 

Leone, 1970). However, that answer has been challenged in 

more recent reviews of the literature (Dempster, 1981, 1985) 

and will not be discussed in this paper. Another answer 

offered is that metamemory (i.e., children's understanding of 

the memory process) develops (Pressley, Borkowski, & 

O'Sullivan, 1985; Rao & Moely, 1987). That line of research 

also will not be examined in this paper, because it is not 

directly related to the present study. Two other answers to 

the question have received the most attention. They are that 

strategy use develops and that knowledge develops. Each of 
these will be discussed. 

Strategy Use Develops 

One of the answers to the question "What is memory the 
development of?" was emphasized by several presenters at the 
1971 symposium and still is being researched today. That 
answer is that strategy use develops. Theoretical models 
from the 1970s and up through the early 1980s (if not 
longer) also emphasized strategies (Ackerman, 1987). 

In 1970 an influential article by Flavell proposed that 
younger children have a production deficiency. That is, 
younger children typically do not employ strategies for 
remembering (e.g., rehearsal) spontaneously. However, if 
younger children are instructed to use the strategy, their 
recall rises to the same level as older children, who 
spontaneously produce the strategy. 

A surge of research investigated that hypothesis. 
Improvements with age in strategies such as rehearsal (e.g., 
Flavell, Beach, & Chinsky, 1966; Ornstein, Naus , & Liberty, 
1975); clustering (e.g., Moely, Olson, Halwes, & Flavell, 
1969; Moely & Shapiro, 1971); organization (e.g., Corsale & 
Ornstein, 1980; Kee & Bell, 1981); and elaboration (e.g., 
Pressley, 1982; Pressley & Ross, 1984) are well documented. 
Training studies also reliably show that younger children 
benefit by brief instruction in rehearsal (e.g., Naus, 

Ornstein, & Aivano, 1977; Ornstein, Naus, & Stone, 1977); 
clustering (e.g., Moely et al . , 1969); organization (e.g., 
Bjorklund, Ornstein, & Haig, 1977; Moely & Jeffrey, 1974); 
and elaboration (e.g., Pressley et al . , 1985). 

An example of a study from this period follows. This 
study by Moely et al. (1969) was interpreted as confirming 
that younger children have a production deficiency. Children 
in grades 1, 3, and 5 were presented with 16, 20, or 24 
pictures of categorically related items (i.e., 4, 5, or 6 
items from the categories of animals, furniture, vehicles, or 
clothing) to study for two minutes. There was greater 
categorical organization with increasing age. Although there 
was little change between grades 1 and 3 in the children's 
study and recall organization, there was a sharp increase in 
both measures between grades 3 and 5 . An instructions 
condition, during which children were asked to sort the items 
"that go together or are alike" (p. 28), facilitated the 
performance of all children. Furthermore, after recall, when 
nonsorters (children who had not been instructed to sort) 
were asked to sort the pictures, 58%, 74%, 88%, and 95% of 
the kindergarten, first, third, and fifth graders, 
respectively, were able to sort the cards according to their 
category membership. Thus, nonsorters were able to sort. 
The fact that these young children were able to sort cards 
according to category membership was interpreted to mean that 

they possessed the necessary knowledge about categories, but 
simply did not use it. 

Much like the Moely et al. study, the other studies of 
this period seemed to confirm that although younger children 
(i.e., children in grades 1 to 3 ) often did not utilize the 
appropriate strategies spontaneously, they easily could be 
taught to use them, and consequently, benefited from them. 
By grades 5 to 7 , children employed strategies spontaneously 
and successfully. 

More recently, several aspects of the production 
deficiency hypothesis have been questioned. Chi and Ceci 
(1987) challenged the assumption that young children have the 
relevant knowledge about categories but simply do not use it. 
Although the young children in the Moely et al. study (as 
well as other studies of that period) were able to 
successfully complete sorting tasks, and the researchers 
claimed this was evidence that the children had the necessary 
knowledge, Chi and Ceci suggested that children's knowledge 
simply may not be in a readily usable form. They gave the 
example that picking pictures that belong to the category 
"animals" only requires a child to know whether the 
attribute of "animalness" goes with each item. They believe 
that this type of knowledge is different from the knowledge 
needed to link elements to a unified superordinate structure. 
That is, a child who can sort or match may have a 
representation that is not a categorical structure. 

Therefore, the child's and adult's representations of 
knowledge still might differ dramatically with respect to 
organization, and these differences might make the knowledge 
less available to children. 

Rabinowitz (1984) has argued for the importance of 
differentiating between whether young children do not use 
available knowledge because they prefer not to use it or 
because it is less accessible to them. Although the 
traditional notion of production deficiency claimed that 
young children were predisposed to use strategies (such as 
repeating a word over and over) that were less effective in 
helping them recall, Rabinowitz suggested that those 
strategies might be more easily accessed than one of 
organizing words by semantic meaning. He demonstrated that 
children use categorical processing more effectively when 
the list contains highly representative items from the 

A second question concerns the way in which strategies 
develop. Several studies stimulated by the production 
deficiency hypothesis have demonstrated what appear to be 
strategic behaviors by preschoolers (e.g., Baker-Ward, 
Ornstein, & Holden, 1984; DeLoache, Cassidy, & Brown, 1985; 
Wellman, in press). This might seem to challenge the claim 
that young children do not spontaneously produce strategies. 
However, these occur only in specific, supportive contexts. 
It is not clear how and why early strategic behavior emerges 

(see also a review by Daehler & Greco, 1985), and how it 
relates to mature strategy use, which appears to be more 
general. Researchers currently are debating whether 
earlier strategies are deliberate and intentional or 
relatively unconscious and automatic. This and other debates 
in the field will be addressed in a later section. 

Even if younger children produce the same strategy as 
older children, it may be, as suggested in a study by 
Guttentag (1984), that strategy use is more effortful for 
younger children. This may account for the observed lags in 
the facilitative effects of early strategy use for younger 
children (e.g., DeMarie-Dreblow & Miller, 1988; Miller, 
Haynes, DeMarie-Dreblow, & Woody-Ramsey, 1986). These 
children spontaneously produce an appropriate strategy, but 
it does not help them, a phenomenon that Patricia Miller has 
labeled a "utilization deficiency" (Miller & Harris, in 
press). If producing a strategy is quite effortful for young 
children, there may be little capacity remaining for 
subsequent processing of the material to be remembered. 
Thus, as these studies illustrate, clarifications of the 
mechanisms by which strategies develop are necessary. 

Although debates exist as to the development and nature 
of strategies, probably no one in the late 1980s still 
believes that strategy use alone can explain what develops 
when memory develops. Another view of memory development, 
which is receiving greater and greater attention from 

researchers, suggests that knowledge plays an important role 
in memory development. 

Knowledge Develops 

A study by Chi in 1978 posed a major challenge to the 
field of memory development research. She showed that when 
younger children had more knowledge of a domain (e.g., 
knowledge of chess) than adults, the superiority of the older 
subjects, typically found in other studies, was absent. In 
fact, the 10-year-old children in Chi ■ s study (who were chess 
experts) recalled more chess piece positions from immediate 
memory and took fewer trials to recall all chess piece 
positions, than the adults (who were chess novices). The 
children also retrieved a greater number of chunks than the 
adults for the first trial. On the other hand, Chi found the 
more typical adult superiority for a digit span task. She 
proposed that knowledge of the specific content area was more 
important than general strategies in determining memory 
performance. Thus, Chi ' s answer to the question "What is 
memory the development of?" was that knowledge develops. 

A study by Lindberg (1980) found similar results. Third 
graders and college students were tested for recall of two 
different lists, each containing 30 words. One list was a 
typical experimental list that contained words from Battig 
and Montague category norms. The other list contained words 
generated by three third graders. These words were assumed to 


be highly familiar to third graders. An example was the 
members of the television show "Charlie's Angels," something 
of importance to most third graders in 1980! Although the 
college students clustered and recalled more of the words 
typically used in experiments, the third graders clustered 
and recalled more of the words that were more salient to 
them. Again, a reversal of the traditional superiority of 
adults seemed to show that knowledge of the stimuli was an 
important aspect of memory development. 

This wave of research in the late 70s and thus far in 
the 80s has attempted to define the role of knowledge in 
memory performance. Differences in knowledge were said to be 
responsible for both differences in the production of a 
strategy (e.g., rehearsal) and memory per se in a study by 
Naus and Ornstein (cited by Zembar & Naus, 1985a). Naus and 
Ornstein tested two groups of adults (soccer experts and 
soccer novices) for recall of two different lists of words (a 
typical experimental list and a list containing soccer- 
related items). Although there were no significant 
differences between the two groups for recall and size of the 
rehearsal set (i.e., the average number of different words 
rehearsed aloud per inter-item interval) for the typical 
experimental list, the soccer experts were superior on both 
measures for the soccer-related item list. Because adults 
presumably already have sophisticated memory strategies 

accessible to them, the results were attributed to the 
differences in knowledge of the materials for recall. 

Likewise, a study by Zembar and Naus (1985b) found 
differences in the level of strategy use and recall, 
depending upon the materials. They gave third graders, sixth 
graders, and adults lists that varied in familiarity to them 
and found corresponding differences in rehearsal strategies 
and recall. When third and sixth graders were studying a 
list that was very familiar to them, they used a more 
sophisticated rehearsal strategy (i.e., rehearsing a greater 
number of different items together) than when they were 
studying a list that was less familiar to them. An 
interesting result in this study was that the third graders' 
rehearsal and recall of the easiest list was almost identical 
to the sixth graders' rehearsal and recall of the typical 
experimental list. On the other hand, the sixth graders' 
rehearsal and recall of an advanced adult list was as poor as 
the third graders' rehearsal and recall of the typical 
experimental list. Thus, these studies suggested that 
knowledge of the materials to be learned could influence the 
use of strategies, which then could influence memory 

In the words of Zembar and Naus (1985a): 

In a "short-term" fashion, the available empirical 
evidence suggests that age-related changes in knowledge 
can affect the ease with which strategies are employed 
by modifying the actual content in knowledge as well as 
increasing the ease by which information can be 
accessed, (p. 7) 


It has become obvious to researchers investigating 
memory development in the 19 80s that no single, simple 
answer to the question "What is memory the development of?" 
is likely to be found. It appears to be more and more likely 
that knowledge and strategies interact. Recently, 
researchers have begun to debate several aspects of strategy 
usage and knowledge. Because these provide a context for the 
current study, they are explored in the next section. 

Current Debates in the Field of Memory Development 
Accompanying the important question of what is 
developing are recent debates about various issues 
concerning the nature of strategies and knowledge. One 
debate concerns whether strategy use during the grade school 
years is deliberate and intentional or automatic and 
unconscious. Another debate concerns the nature of knowledge 
and why greater knowledge may facilitate the use of 
strategies. Discussions of both follow. 

Currently, the main debate concerning the nature of 
strategies and their use is between Peter Ornstein and David 
Bjorklund. Ornstein, Naus, and others take the position that 
strategy use develops much like skills develop (see Ornstein, 
Baker-Ward, & Naus, in press; Zembar & Naus, 1985a). They 
believe that the cognitive operations required for the 
successful deployment of strategies gradually become more 
routinized. As this happens, strategies require less and 

less capacity with age, and, consequently, during development 
they facilitate children's performance to a greater extent 
when they are employed. Ornstein, Naus , and others also 
distinguish between strategies at input (e.g., rehearsal and 
organization) and strategies at output (e.g., clustering). 
Finally, they claim that even preschoolers show strategic 
behaviors when learning very familiar material, and that even 
these behaviors may be intentional and deliberate. 

Bjorklund, on the other hand, disagrees with the 
position of Ornstein, Naus, and others. He believes that 
strategy use, and particularly the clustering that typically 
is observed in children's recall, is not deliberate until 
early adolescence (see Bjorklund, 1985). He claims that the 
clustering typically observed in younger children's recall is 
due only to the automatic activation of associated words in 
memory. This position also was taken by Lange (1973,1978), 
who included lists that minimized the associativity of words 
and found that younger children's clustering was no longer at 
above-chance levels. 

Other evidence for that position came from research by 
Bjorklund and Zeman (1982,1983). When children in first, 
third, and fifth grades were asked to recall their 
classmates' names (information that is quite familiar to 
them), memory performance was high for children of all ages. 
Although clustering (i.e., organizing recall by seating in 
the classroom, reading groups, race, or sex) also was a I a 

high level, the majority of children were not able to state 
what strategies they had used to remember the information. 
This was taken as evidence that early clustering is based 
upon associative relations, and that strategies later are 
discovered when subjects notice patterns of their own 

Consistent with Bjorklund's position is the finding that 
grade school children, who appear to be clustering at above- 
chance levels, in fact do so minimally. Frankel and Rollins 
(1982) attempted to explain why children who are under eight 
years of age who had above-chance clustering did not 
necessarily have enhanced levels of recall. Whereas the 
younger children's recall typically consisted of isolates or 
of only two intracategory items, adults' recall consisted of 
category strings, with as many as five or six items per 
string. The results were interpreted as evidence that the 
organization of children's and adults' recall differs 
dramatically, and that children's clustering in recall may be 
associative rather than categorical. 

Bjorklund (1987) proposes that a major developmental 
change is the increased frequency of occurrence of particular 
items. He argues that more frequent exposure to certain 
items probably causes an increase in the number and type of 
features and creates more links with other items in semantic 
memory. This, he believes, is largely responsible for the 
changes with age in the ease with which semantic memory items 


can be activated. In a more recent review of the literature, 
Bjorklund and Muir (in press) further suggest that when items 
in semantic memory can be activated more easily, children 
have more mental capacity available for other cognitive 
operations (e.g., memory strategies). Bjorklund (1987) also 
cautions that one must be careful not to define the term 
"knowledge" too broadly when referring to differences in 
knowledge base across ages. 

The Definition and Measurement of Knowledge 
Although the focus of many current studies of memory 
development is on differences in knowledge, very few have 
given much attention to a) quantifying the knowledge or b) 
comparing the recall of individuals with moderate differences 
in knowledge. Many studies simply classify individuals as 
experts or novices (Chi, 1978; Gobbo & Chi, 1986; Naus & 
Ornstein, cited by Zembar & Naus, 1985a), neglecting the 
relative degree of knowledge present. Although the knowledge 
differences in which developmentalists are interested 
primarily are those involving a moderate variation in type or 
degree, most studies investigating knowledge effects define 
knowledge in terms of only two points on the continuum, 
typically very advanced or very elementary knowledge. 
Saarnio (1987) claims that studies of this nature inflate 
the role of knowledge. During the tenth anniversary 
symposium of Flavell's 1971 symposium, Olson (198 3) noted 

that there still were several important clarifications to be 
made in the field of memory development, one of which was to 
determine more subtle differences between experts and 
novices, beyond the obvious one that the expert knows more 
about the topic than the novice. There may be qualitative 
changes (i.e., changes in organization) occurring that go 
beyond the simple differences in amount of knowledge when 
expertise reaches the highest level, but this cannot be 
determined unless attempts first are made to quantify 

Other studies compare words that are presumed to be more 
familiar to one or more groups than others (Lindberg, 1980; 
Zembar & Naus, 1985b) or compare recall for more typical 
versus atypical members of categories (Bjorklund, 1988; 
Bjorklund & Thompson, 1983; Buchanan & Bjorklund, 1988). All 
of these studies measure knowledge at two points at the upper 
end of the continuum, that is, knowledge that is extremely or 
moderately well-learned. Again, knowledge has not been 
measured along a continuum. Therefore, the challenge for 
memory development researchers in the 1990s will be to 
specify exactly what is meant by knowledge and exactly what 
are the actual mechanisms by which memory improves . Very few 
studies have attempted to examine the contents of knowledge 
to date. 

One study quantified the meaningfulness of three letter 
nonsense syllables (trigrams) by having subjects generate as 

many associations for each as possible. Differences in 
recall also were measured. It was found that differences in 
recall could be explained by differences in meaningfulness 
(Richman, Nida, and Pittman, 1976). However, because the 
recall test consisted of non-words, it is difficult to 
generalize the results with certainty. Using a similar 
measure but with real words (i.e., requiring adults to 
generate as many facts as they knew for each of 45 birds), 
DeMarie-Dreblow (1988) found a different outcome. Degree of 
meaningfulness did not correlate significantly with adults' 
recall for birds. 

Chi and others conducted research specifically designed 
to describe the structure of knowledge in memory. For 
example, Chi and Koeske (1983) compared the knowledge 
structures of two subsets of a knowledge domain that one 
child possessed. They utilized the model of memory proposed 
by Collins and Quillian (1969), which assumes that concepts 
are stored in memory as nodes on an associative network, and 
relations between concepts serve as associative links. Their 
subject, a 4 1/2 year old boy, was an expert on the subject 
of dinosaurs. They compared the way that familiar dinosaurs 
were structured in his memory to the way that less familiar 
dinosaurs were structured. 

The first task entailed having the child generate all 
the names of dinosaurs he could. He produced 4.6 distinct 
names over a two week period. Next, the experimenter and 

child switched roles in a clue game, during which one person 
told a list of properties and the other had to identify the 
dinosaur which possessed those properties. Then, two lists 
of 20 dinosaurs were presented at the rate of one word every 
three seconds for the recall task. Finally, one year later, 
a recall naming task was presented to test his memory. The 
child was shown pictures of dinosaurs and asked to name them. 

Chi and Koeske's results showed that the dinosaurs that 
were more familiar to the boy had a greater average number of 
links associated with each one, and that these dinosaurs had 
a greater number of intra-group links with very few, if any, 
inter-group links. Whereas the boy recalled 10, 8, and 9 
dinosaurs across trials from the more familiar list, he 
recalled only 6, 4, and 3 dinosaurs from the less familiar 
set. One year later, the boy named 11 of the 20 familiar 
dinosaurs when shown picture cards, but named only 2 of the 
20 less familiar dinosaurs correctly. Chi and Koeske 
concluded that the observed differences were due to the 
difference in the structure of knowledge in semantic memory. 
They suggested that the knowledge of the more familiar set of 
dinosaurs was more cohesive. 

Although this study measured both knowledge and memory, 
there was only one subject. Therefore, it is difficult to 
generalize these results with any confidence to all children, 
or to be certain that they explain memory development in 
general . 

In another study, Gobbo and Chi (1986) utilized 
production and sorting tasks to compare the underlying 
knowledge structures of five experts and five novices in the 
domain of dinosaurs. Expertise was determined via a pretest, 
and all children were seven years old. For the production 
task, children said the name of each pictured dinosaur and 
told everything they knew about it. The number of explicit 
propositions (i.e., propositions based solely on information 
that could be gained from the picture) versus implicit 
propositions (i.e., propositions that gave interpretations or 
made reference to information that could not be directly 
observed in the picture) was determined from the children's 
protocols. Whereas the two groups did not differ in their 
use of explicit propositions, the experts used a 
significantly greater number of implicit propositions than 
the novices. Furthermore, on the sorting task, experts were 
less likely than novices to group the dinosaurs on the basis 
of explicit physical features. Instead, experts tended to 
group the dinosaurs on the basis of combinations of 
attributes, resulting in family distinctions in many cases. 

Gobbo and Chi emphasized that experts and novices differ 
in their representations, particularly in that experts tend 
to focus on "deep-level," rather than "surface-type," 
features. Experts' knowledge also tends to be more 
structured and cohesive. Chi and Koeske suggested that these 
differences in knowledge are responsible for the differences 

that have been observed in the way experts and novices use 
their knowledge. However, neither a memory test nor any 
measurement of strategies was included in this study, so it 
is difficult to relate these results to issues of memory 
development . 

Although Chi (1985) interpreted the recall differences 
in the Chi and Koeske study as resulting from domain-specific 
strategies, Ornstein and Naus (1985) cautioned that the study 
neither defined nor measured particular strategies. 
Furthermore, they claimed that it is important to 
differentiate the contents of knowledge from the ease with 
which that knowledge can be retrieved from memory. Current 
research does not differentiate between these two aspects of 
a knowledge base. In fact, there have been no systematic 
studies of relations among knowledge, strategy use, and 

Purpose of this Study 
Many aspects of this study differed from previous 
studies of memory development. These differences were as 
follows . 

1. Previous research was correlational (i.e., examined 
relations between memory and pre-existing differences in 
knowledge). In contrast, this study examined the claim that 
knowledge causes improvements in strategy use and memory by 
experimentally manipulating knowledge (i.e., constructing new 

knowledge). To the writer's knowledge, this is the first 
experimental test of that hypothesis. Because correlation 
need not imply causality, such a test is essential. After 
pretests for knowledge of, or memory for, birds, knowledge 
was manipulated by showing children videotapes about birds. 
If the claims of previous research are correct, then 
increases in knowledge should be accompanied by increases in 
both study strategies and recall. 

2. Previous research did not measure knowledge along a 
continuum, but instead tended to select subjects who 
represented the endpoints (i.e., experts and novices) of 
knowledge. In contrast, this study measured moderate levels 
of knowledge. 

3. Previous studies generally included only a single 
measure of knowledge. However, as is clear from the debate 
on the nature of knowledge described earlier, there may be 
different aspects of knowledge, which may differ in their 
effects on memory. Thus, this study included four different 
knowledge tests, each of which quantified knowledge. 

The first test was similar to the sorting task utilized 
by Chi and Koeske (1983). Children were asked to group birds 
that were alike or went together in some way. Based on Chi 
and Koeske 's differentiation between explicit and implicit 
propositions, this study included a count of the number of 
birds that were placed into meaning-based groups (i.e., 
groups formed on the basis of information that could not be 

obtained by information that appeared in the pictures of 
birds ) . 

The second knowledge test was similar to the measure of 
production in Chi and Koeske's (198 3) study. Children were 
asked to generate as many birds as possible that belonged to 
each of six different experimenter-designated categories. 
The total number of birds correctly generated by a child for 
these categories was tallied. 

The third knowledge test was similar to Richman, Nida, 
and Pittman's (1976) measure of meaningfulness . Children 
were asked to generate as many facts as they knew for each 
bird. The total number of correct facts generated by a child 
and the total number of birds for which a child knew at least 
one fact were calculated. Then, the nature of the generated 
facts was examined to determine whether a larger percentage 
of the facts referred to more general, categorical 
information after children watched the videotapes. 

The fourth, and final, knowledge test was a matching 
test. Children decided to which of six categories each bird 
belonged. This test only required knowledge of which 
category "attribute" best described each bird, so it was 
similar to the measures of knowledge reported in early 
research on children's use of organizational strategies 
(e.g., Moely et al., 1969). 

4. Although researchers claim that the structure of 
knowledge may influence the way that knowledge is used, 

again, no one has tested that hypothesis experimentally. For 
example, Gobbo and Chi (1986) found that experts had more 
intra-group and fewer inter-group connections in memory than 
novices. They hypothesized that the fact that experts' 
knowledge was more tightly structured might make that 
knowledge more accessible to them. 

The domain of birds was chosen because it seemed to be 
an area about which everyone would know something. Yet, 
knowledge of birds was expected to be highly variable, with 
some individuals knowing quite a bit and others knowing very 
little. Therefore, it appeared to be an area in which 
knowledge would fall along a continuum. Also, birds can be 
classified on a simple physical (e.g., size of beak) or more 
conceptual basis, much like the dinosaurs were in the work of 
Chi and others. 

In this study, videotapes about birds were shown to 
children to attempt to create knowledge that was more tightly 
structured. Lessons about birds taught intra-group 
associations (i.e., associations were made between that bird 
and two other members of the bird's group) in an effort to 
see if creating the stucture of that type of knowledge would 
facilitate strategy usage. 

Much as in Lange's studies (197 3, 1978), the 
associativity of words on the recall lists was minimized by 
not placing words commonly clustered by children and adults 
in pilot research on the same list. Therefore, this would 

reduce the words clustered due to their associativity and 
enhance the possibility of detecting clustering due to 
category relatedness. in turn, any changes in clustering 
would more likely be due to the teaching about birds on the 
videotapes. To insure that any improvements would not be due 
only to experience with particular items, children received a 
different list to recall on the pretest and posttest. 

5. Most of the previous research focused upon knowledge, 
or a single study strategy, and recall. To date, no 
systematic study of all three (knowledge, strategy use, and 
recall) has been conducted with a large number of subjects. 

In this study, children in grades 2 through 5 
participated. Previous research suggests that children begin 
to use more active study strategies sometime during those 
years. Children were videotaped during the study time for 
the memory test, and several overt study strategies (i.e., 
rehearsal, self -testing, and involvement with the cards such 
as touching or moving them) were identified. In addition, a 
measure of clustering during recall was assessed. Like other 
studies (e.g., Moely et al., 1969), the memory test was a 
recall test. After children studied 20 picture cards of 
birds for two minutes, they were asked to recall them in any 
order. Thus, this study was comprehensive and included 
measures of knowledge, memory, clustering, and study 


There were three major hypotheses in this study. The 
first hypothesis concerned the measurement of knowledge. It 
was hypothesized that knowledge, as measured by each of the 
four knowledge tests, would improve significantly after the 
children watched the videotapes about birds. 

Second, as mentioned previously, current theories 
suggest that changes in knowledge may be responsible for 
improvements in both strategy use and recall with age. If 
this were the case, then improvements in knowledge should be 
accompanied by more active use of study strategies, and 
improvements in clustering and recall. If changes in 
strategy use and recall were not found, that would question 
whether there was a causal relation between knowledge and 

Whether or not strategy use and recall improved 
significantly, the third hypothesis was that there would be 
positive correlations among knowledge, strategy use, 
clustering, and recall. This would support previous 
research. However, whether the relation among them would 
change with age was not known. 



Parent permission letters were sent home with 124 
children attending a private school in Gainesville, Florida. 
As suggested by the fact that the tuition for one year was in 
excess of two-thousand dollars, the children generally were 
from middle-or upper-middle class families. Nearly all were 

Parents of 97 children consented to participation in the 
study. There were 9 males and 12 females from second grade 
(mean age: 8-1), 14 males and 9 females from third grade 
(mean age: 9-2), 14 males and 18 females from fourth grade 
(mean age: 10-1), and 11 males and 10 females from fifth 
grade (mean age: 11-1). 

Each classroom teacher rated her students' ability to 
learn in school by assigning a descriptive number from one 
(low) to three (high). Children within each grade, sex, and 
achievement rating were assigned randomly to groups with the 
constraint that each group contain children with 
approximately equal mean ratings. 




Picture cards were utilized for the memory and grouping 
tests. Each of the 45 three by five inch cards contained a 
black line-drawing of a bird in the center and a label with a 
single word naming the bird at the bottom (e.g., "owl" for 
great horned owl). Because all birds' pictures were black 
and white and were drawn to be approximately the same size, 
there were no size or color cues provided by the cards. 

The picture cards for the memory test had a pale blue 
background, and the naming-label appeared on a small, white 
strip. The picture cards for the grouping test were xerox 
copies of the others. Thus, these were only black and white. 

Pilot testing of children in grades 3 to 6 at a 
different school was conducted in order to develop two 
different lists of 20 birds (see Appendix A) to be used for 
the memory test. Based on the pilot data, these lists had 
approximately the same probability of recall. In addition, 
birds that tended to be clustered together by college 
students (determined by other pilot testing) were placed on 
different lists. With lists that contained few commonly 
clustered words, the effect of instruction (giving additional 
knowledge of birds) upon clustering could be examined more 
clearly. Each list contained the same number of members 
(i.e., three or four) that could be classified in each of the 
six categories. The birds belonging to each of the six 
categories were determined by an ornithologist at the Florida 

Museum on the campus of the University of Florida. Thus, 
children who took the memory test twice received different 
(but approximately equal) lists of words, and any improvement 
in recall would not simply be due to recalling the same list 

Children's study strategies during the memory test were 
videotaped with a Sony Camcorder attached to a tripod in a 
corner of the room, approximately 7 feet from the table at 
which children sat. There was no monitor. A stopwatch timed 
both the study period and the time for computing math 
problems. Children's responses during the memory test and 
the facts test were tape recorded. 

A yellow tagboard strip was utilized for the matching 
test. This strip contained one representative picture for 
each of the six categories and keywords for each category 
label (e.g., a picture of waves and "live by the water" or a 
picture of a place setting at a dinner table and "people 
eat") . 

Five 10 to 15 minute videotapes (VIDEO) taught facts 
about 34 of the 45 birds (see Appendix B). Only a subset of 
the tested birds were taught, so that the other birds could 
serve as a control set. Analysis of the control set would 
help to reveal the source of changes in children's 
performance on the tests. If no improvement occurred in the 
control set, then improvements in the set of birds that were 
taught probably were due only to the videotapes. However, if 

improvements were noted on the control set, that might 
suggest that taking the tests alone improved children's 

A graduate student filmed pictures of slides with the 
Sony Camcorder, while a female graduate student narrated the 
lessons. Thus, these videotapes were of the "home video" 

A brief, general introduction to birds was provided at 
the beginning of the first videotape. A brief introduction 
to each of the six categories was given before the first 
member of that category was introduced. Thereafter, no two 
birds from the same category were taught consecutively, and 
there was no explicit teaching of all the birds belonging to 
any specific category. Because this was the first 
experimental investigation of the hypothesis that increases 
in knowledge (via additional intra-group associations and a 
greater number of connections per bird in semantic memory) 
cause improvements in memory, it was important not to 
explicitly teach the categorical structure. If children had 
not been required to do any construction of knowledge 
themselves, any improvements in memory would appear trivial. 

The format for teaching about each bird was similar. 
Each segment began by telling how that bird was similar to 
the one in its category that most closely preceded it. Many 
facts about the bird's habitat, nesting, migration, food, 
mating, song, or peculiar habits were told during the lesson. 


Similarities and differences between that bird and its two 
category members that preceded it most closely were given 
during the lesson, and the lesson ended by explaining 
something unusual about that bird, giving a reminder about 
the bird, or telling a funny story about that bird (see 
Appendix C for sample lessons). The sources consulted for 
information about birds were books (Bull & Farrand, 1977; 
Peterson, 1947; Robbins , Bruun, & Zim, 1966; Steward, 1977; 
Zim & Gabrielson, 1956) and an ornithologist. 

Other cues were provided during the teaching of some of 
the categories. Songbirds' songs were audible during entire 
lessons on songbirds. Pictures of water birds always showed 
the bird on, near, or over the water. Nightbirds' sounds 
were played briefly sometime during the lesson, and either 
their pictures had a dark sky, or the bird was shown 
camouflaged among its natural surroundings. 

Two groups took four knowledge tests or a memory test 
both before and after viewing the videotapes about birds (see 
Table 2-1). A third group took the memory and knowledge 
tests only after viewing the videotapes. This design 
permitted assessment, with appropriate controls, of both 
within-subject and between-subject changes in knowledge, 
memory, clustering, and strategy use. 


TABLE 2-1 

Testing Sequence for Three Groups of Children Tested 
for Their Memory and/or Knowledge of Birds 




Memory Knowledge Memory Knowledge 

Test Tests Videotapes Test Tests 

Test Only 








Within-subject analyses for changes in knowledge 
compared pretest versus posttest scores on the grouping, 
listing, facts, and matching tests of the Knowledge Test Only 
group. Within-subject analyses for changes in memory, 
strategy use, and clustering compared the pretest versus 
posttest scores of the Memory Test Twice group. 

Between-subject analyses for differences in knowledge 
compared the Knowledge Test Only group's pre-VlDEO grouping, 
listing, facts, and matching test scores with the other two 
groups' post-VIDEO scores. Finally, between-subject analyses 
for differences in memory, strategy use, and clustering 
compared the Memory Test Twice group's pre-VIDEO scores with 
the Posttest Only group's post-VIDEO scores. 

The Posttest Only group was included to insure that pre- 
VIDEO testing was not biasing the results. It also was 

important to include it in order to generalize the results 
with confidence to other laboratory experiments. In other 
experiments, subjects typically come to the laboratory with 
pre-existing knowledge. Therefore, it was important to be 
able to show that children's memory for birds and knowledge 
of birds was not simply changing because of a practice effect 
of taking the same tests twice. 

Thus, there were two reasons for designing the study to 
include both within- and between-subject analyses. One was 
the need to include particular controls for repeated testing. 
The second was to facilitate the comparison between this 
study, which attempted to construct knowledge, and previous 
studies, which examined pre-existing knowledge. 


All children were tested individually. Children gave 
their answers for all questions aloud, and the experimenters 
tape-recorded and/or wrote what each child said on the data 
sheets. No tests had time limits. 

The memory test lasted approximately 10 minutes per 
child. The knowledge tests were administered in a different 
session, which always followed the memory test, if it were 
given, and took approximately 35 minutes per child. Most 
children were tested for both memory and knowledge on the 
same day, but for practical reasons several were given the 
knowledge test the day after they took the memory test. 

One male undergraduate student administered all of the 
memory tests, and one female graduate student administered 
all of the grouping and listing tests. Finally, one of two 
female undergraduates, depending upon each one's 
availability, administered the facts and matching tests. 

During the first week, children were tested either for 
their memory for a list of birds via a recall task or for 
their knowledge of birds via four different tasks. After 
three additional weeks had passed, children were shown the 
five videotapes, one per day, in their classroom by their 
classroom teacher. Finally, post-VIDEO tests were 
administered the following (sixth) week. 

Memory Test 

Children entered a small room inside an office complex 
at their school. The experimenter introduced himself and 
told them what they would be doing. He explained that the 
children were being videotaped, so we could compare how they 
played the game to how other children played the game. 

Two pieces of black tagboard sandwiched the array of 20 
picture cards. There were four cards per row and five cards 
per column. Only the corners of the cards touched. 

The experimenter lifted the tagboard, to reveal the 
picture cards, and instructed children to read the name of 
each bird once aloud. If a child mispronounced a bird's 

name, the experimenter pronounced it correctly. Then, the 
tagboard was replaced. 

The experimenter instructed children to study the birds 
in any way they wished for two minutes. He also told them 
(and demonstrated to them) that they could move the cards 
around if they wished. Half of the children studied the 
cards for List A and the other half studied List B. After 
two minutes of study time, the experimenter closed the top of 
the tagboard, so no cards were visible. To eliminate the 
recency effect, children received a sheet of math problems, 
which contained simple addition problems without carrying 
that they computed for 30 seconds. When the experimenter 
said "stop," they were instructed to say as many birds' names 
as they could remember in any order. After 15 seconds of 
silence, the experimenter said, "Can you remember any other 
birds?" After an additional 15 seconds of silence, the 
testing session ended. 

Knowledge Tests 

l. Grouping . Before going to a child's classroom, the 
experimenter shuffled the picture cards and placed them 
randomly into five rows with nine cards in each row on a 
table at which the child would be seated. No more than two 
cards from the same category ever appeared consecutively in 
either direction. Children walked with the experimenter to 
the room, which was upstairs in a loft at their school 


library. While they were walking, the experimenter 

introduced herself and said: 

We're interested in what kids your age know about birds. 
You're going to be doing four different activities. We 
have been doing these activities with adults and find 
that they don't know very much about birds, so don't be 
upset if there are birds you've never heard of before. 

When they reached the room, the experimenter explained 
that the first activity was to decide which of the birds were 
alike or went together in some way. She told children to 
read each bird's name aloud as quickly as possible and 
assisted them with names they could not pronounce. 

As children gave the experimenter birds they thought 
belonged together, she wrote them on a data sheet. Then, 
after asking the children how they thought the birds were 
alike or went together, she wrote the children's chosen title 
for the group on the data sheet too. This procedure 
continued until children had eight groups of birds, used all 
45 birds in groups, or could not think of any other groups 
for the remaining birds, whichever came first. 

2. Listing . After children completed the grouping task, 
the picture cards were removed from the table, and they heard 
the directions for the listing task. The experimenter said 

"Tell me as many birds as you can think of that are " . 

One of the following six categories was read: birds of prey, 
birds people eat, talking birds, birds awake at night, birds 
that live by the water, and songbirds, in that order. The 
experimenter wrote all the birds children said under the 

appropriate category on the data sheet. Children were 
prompted by the experimenter after 15 seconds of silence. 
After an additional 15 seconds of silence, the experimenter 
said the next category. This procedure continued for all the 
categories . 

3. Facts . After the children completed the listing task, 
the experimenter thanked them for doing those activities and 
introduced them to another female experimenter, who explained 
the facts task. Children received three lists of birds 
counterbalanced for order. (Each column of Appendix D was 
printed on a separate piece of paper, so the order could be 
changed.) They said each bird's name aloud into a tape 
recorder, and then said as many facts as they knew about the 
bird. If they did not know any facts about that particular 
bird, they were instructed to say "don't know." The 
experimenter told them not to guess, only to say facts , and 
not to spend too much time thinking about a bird. 

4. Matching . After children completed the facts task, 
the experimenter explained that they would be matching birds 
and categories for the final activity. After placing the 
tagboard strip on their lap, she told the children the names 
of the six categories, simultaneously pointing to each one, 
in turn, on the tagboard display. The experimenter read the 
names of birds from a data sheet (see Appendix E), and wrote 
the numbers that represented each category, as children 
responded. Children pointed to the category to which they 

thought each bird best belonged. They were told to guess if 
they did not know a bird. 

The four knowledge tests always were given in this 
order: grouping, listing, facts, and matching. The grouping 
test had to be first, so that children would not be biased in 
their groupings of birds by the categories they heard on the 
listing and matching tests. Matching could be last, because 
it was a test for knowledge that could not be acquired by 
taking the other tests. 

Before each classroom teacher showed her class the 
videotapes, she told the children to try to remember as much 
information as possible. She told them they would see five 
videotapes about birds over the week, and they would be 
tested the following week. 

Coding and Scoring 
Memory Test 

The number of birds correctly recalled from the list of 
birds was tallied. The criterion used for counting a word 
was that the child had to pronounce at least one syllable 
from the word correctly. For example, "whip" was counted for 
"whip-poor-will." Words were counted only the first time the 
child said them (i.e., no credit was given for repetitions). 

Knowledge Tests 

1. Grouping . The labels children gave to their groups of 
birds were examined. One of three possible designations was 
given to each label. If the label contained information that 
clearly was visible from the pictures of the birds (e.g., 
birds that are black, birds with big feet, birds with small 
beaks), then that label was considered a "physical 
description." If the label contained information that was 
contained in the names of the birds (e.g., birds that end in 
"bird," birds that begin with "s"), then that label was 
considered "sound-based." If the label did not contain any 
information that could be obtained from the picture of the 
bird or the name of the bird (e.g., gamebirds, petbirds, 
colorful birds), then the label was considered "meaning- 
based." The total number of birds a child included in 
meaning-based groups was tallied. Taught birds and control 
birds were scored separately for analysis. Independent 
scorers reached 9 5% agreement when scoring half of the 
subjects' data in this manner. In the event of disagreement, 
a third independent rater scored that child's data. All 
disagreements were resolved in this manner. 

2. Listing . The total number of birds correctly listed 
under the appropriate categories was counted. Appendix F 
displays the answers that were considered acceptable and 
unacceptable for each category. These were determined by an 
ornithologist. All categories except "talking birds" were 

counted. The category "talking birds" was considered the 
control set, because that category, and the birds contained 
within it, was not taught by the videotapes. 

3. Facts . The number of correct facts children gave for 
each bird was tallied, and then the scores for all birds were 
summed. Books about birds (Bull & Farrand, 1977; Peterson, 
1947; Robbins, Bruun, & Zim, 1966; Steward, 1977; Zim & 
Gabrielson, 1956) or an ornithologist were consulted when 
questions about the truth of certain facts were encountered. 
The correlation between the scorings of two independent 
raters of 20 children's data was .97. 

Other measures calculated were the number of birds about 
which children told at least one fact, and the percentage of 
the total correct facts they told that were of a general, 
categorical nature, rather than specific in nature. For 
example, if a child said that a bird "lived by water," "ate 
animals," or "sang a song," those facts were considered 
general, categorical statements. On the other hand, if a 
child said facts such as a bird "lived by the ocean," "ate 
mice," or "sang its name", those facts were considered 
specific in nature, and therefore were not counted. 

4. Matching . Appendix E displays the scoring key 
utilized for the matching test. Again, separate scores were 
obtained for taught birds and the control set of birds. 


The Adjusted Ratio of Clustering (ARC score) was used as 
an index of clustering in the children's recall. Roenker, 
Thompson, and Brown (1971) reported that this measure had the 
advantage of allowing comparisons of relative amounts of 
clustering over trials and across experiments, because it 
reflected the "proportion of actual category repetitions 
above chance to the possible category repetitions above 
chance." (p. 45) The formula for the ARC score is provided 
in Appendix G. 

Overt Study Strategies 

Because it was important to assess spontaneous strategy 
use in this study, only overt strategies could be assessed. 
The two minute study time was videotaped and coded by two 
independent observers, who reached 88% agreement on whether 
each of the four categories of study behaviors occurred for a 
subsample of 40 children (see Appendix H) . Four aspects of 
overt study strategies were coded: involvement with the task 
of remembering, rehearsal, involvement with the cards, and 
self-testing. In the event of discrepancy, a third 
independent rater watched and coded the videotape for that 
child. All disagreements were resolved in this manner. 

Behaviors designated as "strategic" are starred in 
Appendix H. The presence versus absence of each type of 
study behavior (coded as "l" if it had at least one checkmark 

by a "strategic" behavior and "0" if it did not) was 
correlated with recall. In addition, a composite strategy 
score was correlated with recall. A maximum of four points 
(one for each study strategy category) could be earned toward 
the composite score that represented total strategy use. 
This composite score also was utilized to assess whether 
increases in study strategies occurred after children watched 
the videotapes about birds. 


The results are subdivided according to the most 
important hypotheses of this study. The first main question 
was whether children's knowledge of birds increased 
significantly after they viewed the videotapes about birds. 
In accordance with the design of the study, this question was 
answered via both within-subject analyses and between-subject 
analyses . The second important question was whether 
children's memory, clustering, and strategy use changed 
significantly after they viewed the videotapes. The current 
theories about memory development would predict that if 
knowledge changed significantly, then these measures also 
should change significantly. Again, the answer to this 
question was investigated via both within-subject and 
between-subject analyses. The third and final question was 
whether there were correlations among knowledge, strategy 
use, and recall. This relation has been demonstrated by 
previous memory development research. 


Did Knowledge Change? 
Within-Subject Analyses 

The only children used in the analyses for the within- 
subject changes in knowledge were the Knowledge Test Twice 
group (refer to Table 2-1 for the design of the experiment). 
The means and standard deviations for each test are displayed 
in Table 3-1. 

A z-score was computed for each child on each of the 
four knowledge pretests by subtracting the mean for that test 
from the test score a child achieved on that test, and 
dividing that difference by the standard deviation 

TABLE 3-1 

Pre-VIDEO and Post-VIDEO Means and Standard Deviations 

For Each Knowledge Test 

Knowledge Test 























Note: All z-scores were computed using the Pre-VIDEO means 
and standard deviations. 

for that test. Second, an average pretest z-score for each 

child was computed by adding together the child's z-scores 

for each of the four tests, and dividing the sum by four. 

Third, in order to look at possible improvements in 
knowledge, each child's posttest scores for each knowledge 
test were converted to z-scores (according to the pretest 
means and standard deviations so that change would be 
apparent). Finally, average posttest z-scores for each child 
were computed in the same manner as for the average pretest 
z-scores . 

To see if the videotapes caused children's knowledge to 
improve significantly, the overall measures of children's 
knowledge (z-scores) were compared. An Analysis of Variance 
(ANOVA) examined the effects of age (2: older versus 
younger), sex (2), and session (2: pretest versus posttest) 
on the average z-scores. Session was a within-subject 
variable. There was a significant main effect of age, 
F(l,15) = 6.17, p < .05. Older children had higher z-scores 
than younger children. More importantly, however, was the 
fact that z-scores were significantly higher for the posttest 
than they were for the pretest, F(l,15) = 19.30, p_ < .001. 
Thus, as hypothesized, knowledge of birds improved 
significantly after children watched the videotapes about 
birds . 

In order to determine whether or not all knowledge tests 
changed significantly from pretest to posttest, or if some 
groups improved to a greater extent than others, an ANOVA was 
computed for each knowledge test separately. Each 2 (sex) by 
2 (age) ANOVA had repeated measurements on session (2). 

1. GROUPING Test . The ANOVA for the GROUPING test 
scores revealed significant main effects of age, F(l,18) = 
6.23, 2 < - 05 ' and session, F(l,18) = 15.14, p < .01. 
However, there also were significant interactions between 
session and age, F(l,18) = 8.05, p < .05, and session and 
sex, F(l,18) = 5.69, p < .05. 

Follow-up analyses were conducted to investigate these 
interactions. ANOVAs were computed for each age separately. 
Sex was the grouping variable in each, and session was a 
repeated measurement. Whereas older children improved 
significantly from pretest to posttest (means were 16.50 and 
25.83, respectively), F(l,10) = 33.97, p <.001, younger 
children did not (means were 8.70 and 11.10, respectively). 
Other ANOVAs were computed for each sex separately. Each used 
age as the grouping variable and session as a repeated 
measurement. Whereas males improved significantly from the 
pretest to the posttest (means were 11.67 and 21.33, 
respectively), F(l,10) = 22.20, p < .001, females did not 
(means were 14.50 and 16.50, respectively). Therefore, the 
interactions were due primarily to older children and males 
showing more improvement from pretest to posttest in 
categorizing birds as members of meaning-based groups and 
less tendency to categorize birds by physical appearance or 
the sounds of their names. 

A parallel ANOVA was conducted using the number of the 
control set of birds (i.e., those not mentioned on the 

videotapes) that were placed into meaning-based groups. 
Unlike the results for the birds that were taught, no changes 
occurred for any group in the number of control birds that 
were placed into meaning-based groups. Thus, it is likely 
that the increase in the number of taught birds that were 
placed into meaning-based groups was due to the videotape and 
not simply an artifact of repeated testing. 

2. LISTING Test . The ANOVA that investigated the 
influence of age (2), sex (2), and session (2) on listing 
test scores also showed significant main effects of age, 
F(l,18) = 5.75, p < .05, and session, F(l,18) = 84.44, p_ < 
.0001. However, there also was a significant three-way 
interaction between age, session, and sex. Although all 
groups improved from pretest to posttest, some groups 
improved more than others (see Figure 3-1). Younger males, 
F(l,4) = 8.96, p < .05; younger females, F(l,4) = 72.00, p < 
.01; and older males, F(l,6) = 106.67, p < .001, all were 
able to list significantly more birds for each category after 
watching the VIDEO about birds . Although older females were 
able to list more birds after the VIDEO, they did not improve 
significantly (p = .09). Thus, the three-way interaction in 
the ANOVA for listing was due primarily to differential 
improvement within groups . 

A parallel ANOVA using only the number of talking birds 
(i.e., a category about which no information was provided on 


20 r 








"* — 






older males 
older females 

younger females 
younger males 




Pretest and Posttest Listing Test Scores for 
Older Versus Younger Males and Females 

the videotapes about birds) that children listed before and 
after the videotapes confirmed that no significant 
improvement occurred in this control measure for any group. 
Thus, the observed changes in the taught birds probably were 
not simply an artifact of testing. 

3. FACTS Test . The ANOVA for the total number of facts 
generated for the 45 birds had neither significant main 
effects nor significant interactions. Children's ability to 
list facts for birds was not influenced by the videotapes. 
Likewise, the number of facts known for the control set of 
birds did not change significantly. 

Although the total number of facts known about birds did 
not change, an analysis was conducted to determine whether 
the number of birds about which children knew information 
changed. Did children learn information about birds that 
they did not know before the videotapes? The number of birds 
about which children knew at least one fact was counted and 
used in this ANOVA. This ANOVA also showed no effect of 
session for any group. 

Although the two previous ANOVAs suggested that the 
number of known birds and the number of facts generated by 
children remained constant, a final ANOVA was conducted to 
determine whether the nature of the facts children generated 
changed as a result of watching the videotapes. The 
percentage of facts that were general, categorical statements 
was utilized for this analysis. 

The increase in the number of facts that referred to 
categorical information after children watched the videotapes 
was striking. The percentage of general, categorical 
statements children said for the posttest (M = 62.05) was 
significantly higher, F(l,15) = 14.70, p < .05, than the 
percentage for the pretest (M = 43.16). There were no 
differences among older and younger children or males and 
females. Thus, the type of facts children said differed in a 
more qualitative than quantitative manner. 

4. MATCHING Test . The ANOVA that investigated the 
effects of age, sex, and session on matching test scores 
revealed a significant main effect of session, F(l,18) - 
4.13, p < .05. Children were able to match a significantly 
larger number of birds with their appropriate categories 
after watching the videotapes about birds. The means for the 
pretest and posttest matching tests were 22.09 and 24.09, 
respectively. On the other hand, the control set of birds 
showed no corresponding change in the number of correctly 
matched birds. Again, the change appeared to be due to the 
videotapes rather than an artifact of testing. 

To summarize the within-subject analyses, three of the 
four knowledge tests had significant improvements from the 
pretest to the posttest quantitatively. Older children and 
males improved their ability to group birds by meaning to a 
greater degree than younger children and females. Older 
females did not improve their ability to list birds under 

appropriate experimenter-designated categories significantly, 
but the other groups did. Both males and females improved 
their matching of birds with categories. Although neither 
the number of birds for which children told facts nor the 
total number of facts children could generate changed 
significantly, the nature of the facts children told changed 
from more specific information about individual 
birds to more general, categorical information. Therefore, 
knowledge did improve, especially for older children and 
males, and in a both a quantitative and qualitative manner. 

Between-Subject Analyses 

Preliminary ANOVAs were computed to investigate whether 
there were any differences among the groups on posttest 
knowledge (i.e., posttest z-scores). In order to safely 
assume that the pretest scores of the Knowledge Test Only 
group were representative of children's knowledge of birds, 
and to generalize the results to standard laboratory tasks 
(in which children come to the memory task with pre-existing 
knowledge), it was important to demonstrate that the groups' 
posttest knowledge scores did not differ. Fortunately, the 
results confirmed that there were no significant differences 
among the groups. Therefore, for all between-subject 
assessments for post-VIDEO knowledge, the Recall Test Twice 
and the Posttest Only groups' scores were combined. These 
post-VIDEO knowledge test scores were compared to the pretest 

(or pre-VIDEO) scores of the Knowledge Test Only group (refer 
to Table 2-1 for the design of the study) to assess 
hypothesized differences in knowledge. 

A Multivariate Analysis of Variance (MANOVA) was 
conducted, looking at the effect of age, sex, and time of 
testing (2: pre-VIDEO or post-VlDEO, depending upon the 
group) on the scores for each knowledge test. MANOVA was 
considered the best analysis, because it takes the 
correlations among the tests into consideration. There was a 
significant main effect of age, F(4,80) = 2.77, p < .05. 
Overall, older children had higher knowledge scores than 
younger children. According to the Pillai's Trace statistic, 
there also was a significant main effect of time of testing, 
F(4,80) = 4.53, p < .01. Post-VIDEO scores were higher than 
pre-VIDEO scores. Thus, these results confirm those of the 
previously presented within-subject analyses. 

In order to determine which of the knowledge tests 
demonstrated significant improvement, ANOVAs were computed 
for each knowledge test separately. Every 2 (age) by 2 (sex) 
by 2 (time of testing) ANOVA showed main effects of age: 
F(l,83) = 8.59, p < .05, for grouping; F(l,83) = 4.95, p < 
.05, for facts; F(l,83), p < .01, for listing, and F(l,83) = 
4.91, p < .05, for matching. Older children's scores were 
superior to younger children's scores on every knowledge 
test. The ANOVA for matching also showed a significant main 
effect of session, F(l,83) = 5.29, p < .05. Children were 

able to match a significantly higher number of birds with 
their correct categories after they saw the videotapes (pre- 
VIDEO versus post-VIDEO means were 22.09 versus 24.26, 
respectively). The ANOVA for grouping revealed a significant 
interaction between session and sex, F(l,83) = 4.22, p < .05. 
Follow-up analyses of this interaction supported the results 
of the within-subject analyses for grouping. Whereas boys' 
ability to group birds into meaning-based groups improved 
significantly, girls' ability did not. Listing did not 
improve significantly after the videotapes. 

The three between-subject ANOVAs investigating the three 
different measures for the facts test replicated the within- 
subject analyses precisely. There were no significant 
differences between pre-VIDEO and post-VIDEO scores 
representing the total number of facts generated by children 
or the number of birds for which children knew at least one 
fact. On the other hand, the percentage of facts that were 
general, categorical statements was significantly higher for 
the post-VIDEO (M = 57.94) than the pre-VIDEO (M - 43.16) 
test. Thus, grouping and matching knowledge improved from 
pre-VIDEO to post-VIDEO testing, especially for boys, and 
children's fact generation changed in a gualitative manner. 

Did Recall, Clustering, and Strategy Use Change? 
Within-Subject Analyses 

Analyses for within-subject changes in recall, 
clustering, and strategy use compared the pretest and 
posttest scores of the Memory Test Twice group (see Table 2-1 
for the design of the study). Current theories of memory 
development would predict that if children's knowledge of 
birds improved significantly, then recall, clustering, and 
strategy use should also improve. 

l. Memory Test . Preliminary analyses showed no 
significant differences between recall of List A or List B. 
Therefore, children who recalled both lists were combined for 
subsequent analyses. An ANOVA was computed to assess the 
effects of age (2), sex (2), and session (2: pretest versus 
posttest as a within-subjects variable) on the memory test 
scores. There was a significant main effect of sex, F(l,39) 
= 7.16, p < .05, with boys recalling more words than girls, 
overall. There also was a significant sex by session 
interaction, F(l,39) = 10.99, p < .01 (see Table 3-2). 

Follow-up ANOVAs looked at the effect of age and sex on 
recall for each session separately. Whereas boys recalled a 
significantly higher number of birds than girls on the 
pretest, F(l,39) = 19.07, p < .001, there were no differences 
between boys' and girls' recall on the posttest. Additional 
follow-up ANOVAs looked at the effects of age and session on 
recall separately for boys and girls. Despite the fact that 


















TABLE 3-2 

Means (and Standard Deviations) of Pretest and Posttest 

Recall for Males and Females in the 

Memory Test Twice Group 

Sex n Pretest Recall Posttest Recall 

Males 21 
Females 22 

only boys gained significantly more knowledge of birds on the 
grouping test after the VIDEO, and boys' improvement was, at 
minimum, equal to girls' improvement, it was only the girls 
who improved significantly on the memory test. This finding 
was contrary to what would have been predicted by current 
memory development theories . 

2. Clustering . It would not make sense to consider 
change from below chance clustering (ARC scores less than 
zero) to chance clustering (ARC scores equal to zero) as 
improvement. Therefore, for the purpose of analyses of 
changes in clustering, ARC scores less than or equal to zero 
were all set to equal zero. A score of zero meant that no 
identifiable clustering was present in the child's recall. 
An ANOVA was conducted to investigate the influence of age 
(2), sex (2), and session (2) on the ARC scores. Although 
current research debates whether clustering reflects a 
deliberate strategy or automatically activated associations, 
the fact that intra-group associations were emphasized in the 

videotapes would lead one to predict that clustering would 
improve after the videotapes, whether or not children were 
aware of clustering as a strategy. However, this was not the 
case. There was neither a significant main effect of 
session nor any significant interactions involving session. 

3. Strategy Use . An ANOVA was computed to see if there 
were any effects of age, sex, and session on children's 
composite strategy scores (i.e., involvement with the task, 
rehearsal, involvement with the cards, and self-testing). 
Appendix H provides the behavioral descriptions for the 
strategy categories which comprised the composite score. 
Again, current research would predict such changes when 
children's knowledge increased. However, the results showed 
no significant main effects and no significant interactions. 
Therefore, like clustering, strategy use did not change for 
any group. 

Between-Subject Analyses 

As was the case for the knowledge tests, preliminary 
analyses showed no significant differences among the groups 
on posttest memory test scores. The only two groups compared 
were the Memory Test Twice group and the Posttest Only group, 
because the Knowledge Test Only group did not take the memory 
test (refer to Table 2-1 for the design of the study). 
Therefore, for the between-subject analyses, the pre-VIDEO 

scores of the Memory Test Twice group were compared with the 
post-VIDEO scores of the Posttest Only group. 

1. Memory Test . Preliminary analyses revealed no 
significant difference between the memory test scores for 
children who studied List A versus those who studied List B. 
Therefore, further analyses did not include list as a 

An ANOVA examined the effects of age, sex, and time of 

testing (pre-VIDEO versus post-VIDEO) on the memory test 

scores. There were neither significant main effects nor 

interactions. These results again were contrary to what 

would have been predicted by current memory development 

theories . 

TABLE 3-3 

Means (and Standard Deviations) of Pre-VIDEO and Post-VIDEO 
Clustering for Younger and Older Children 


Age Clustering Clustering 

Younger .29 .06 

( .36) ( .10 

Older .21 .27 

( .25) ( .30 

2. Clustering . The ANOVA that investigated the effects 
of age, sex, and time of testing on clustering revealed only 
a significant age by time of testing interaction, F(l,67) = 
4.26, p < .05 (see Table 3-3). Contrary to the expected 
improvement in clustering predicted by current theory, the 

interaction was due to the significant decreases in 
clustering by younger children after the videotapes, F(l,30) 
= 4.52, 2 < .05. The older children's clustering remained 
unchanged by the videotapes. 

3. Strategy Use . Supporting the within-subject analyses 
of strategy use, the ANOVA that investigated the influence of 
age, sex, and time of testing on children's overt strategy 
use showed neither significant main effects nor significant 
interactions. This, too, was contrary to what would have 
been expected by current theory. 

Individual-Subject Analysis of Changes 
in Knowledge and Memory 

Because group means do not always accurately reflect the 
performance of individuals, an individual-subject analysis of 
changes from the pretest to the posttest for all knowledge 
tests and the memory test was conducted. This analysis was 
expected to reveal whether the significant changes in pretest 
to posttest scores were due to a substantial number of 
children's test scores improving, or if they were due only to 
a few children who improved substantially. An individual- 
subjects analysis also was expected to reveal whether the 
lack of significance for the memory test was due to few 
subjects improving, or whether most subjects improved but 
only by a few points. Table 3-4 reveals that at least 50% of 
the younger children's scores improved for every knowledge 


TABLE 3-4 

Individual-Subject Analysis for Patterns of Changes 
on the Knowledge and Memory Tests by Age 

Direction of AGE 

Change from Younger 3 Older' 

Pretest to Posttest 


Grouping Test 





Listing Test 





Facts Test: Total 





Facts Test: Number 





Facts Test: Type 





Matching Test 





Memory Test 43 (2.10) 33 (2.00) 

Same Score 

Grouping Test 40 

Listing Test 10 

Facts Test: Total 

Facts Test: Number 20 

Facts Test: Type 11 

Matching Test 10 17 

Memory Test 24 3 3 


Grouping Test 40 (4.25) 

Listing Test 8 (3.00) 

Facts Test: Total 40 (11.25) 58 (5.86) 

Facts Test: Number 20 (3.50) 22 (6.00) 

Facts Test: Type 11 (5.20) 

Matching Test 40 (1.25) 25 (2.00) 

Memory Test 33 (2.90) 33 (1.70) 

Note: Numbers reflect the percentage of children at each age 
whose pretest to posttest scores were in the stated 
direction. The average improvement or regression for 
the group is in parentheses . 

a n = 10 for the knowledge tests and n = 21 for the memory 

" n = 12 for the grouping, listing, and matching tests, n = < 
for the facts test, and n - 21 for the memory 

test measure except grouping, and at least 50% of the older 
children's scores improved for every knowledge test measure 
except the total facts generated. Especially noteworthy were 
the improvements by 100% of the younger children (an average 
of 16.79 percent) and 78% of the older children (an average 
of 27.01%) on the percentage of generated facts that referred 
to general, categorical information. 

In contrast to the knowledge tests, the pattern for the 
memory test appeared to be due more to chance variation than 
to consistent but small improvements by the majority of 
children. There were approximately two points difference 
between pretest and posttest scores on the average for both 
children showing improvement and children showing regression 
on the memory test. 

Were There Significant Correlations Among Knowledge, 
Clustering, Strategy Use, and Memory ? 

Correlations were computed between each of the knowledge 

test scores, clustering (ARC scores), or composite strategy 

use scores, and the memory test scores for younger children, 

older children, and all children (see Table 3-5). Although 

the correlations between each knowledge test and recall were 

significant for the sample as a whole, the correlations were 

higher for older than for younger children. Multiple 

regression analyses were computed for post-VlDEO memory test 

scores as a function of the four knowledge tests for each age 


TABLE 3-5 

Post-VIDEO Correlations Between Knowledge, Clustering, 
or Strategy Use and Recall for Groups of Children 











With Recall 



= 41) 













. 38** 













***£<. 001 

separately. Whereas the four knowledge tests explained 26% 

of the variation in older children's memory test scores, 

they only explained 6% of the variation in younger children's 

memory test scores. Therefore, knowledge of an area becomes 

a better predictor of memory with age. 

As Table 3-6 shows, the correlations among the four 

knowledge tests all were higher for older children, with the 

exception of those between listing or matching and facts 

(which were each .02 higher for younger children). The 

largest discrepancy between older and younger children's 

correlations was between the listing and facts tests. Thus, 

older children's knowledge is more inter-related than younger 



TABLE 3-6 
Correlations Among the Knowledge Tests By Age 
























To determine whether clustering predicted recall, two 
Analyses of Covariance (ANCOVA) were computed. Each 
investigated whether clustering predicted recall, while 
controlling for differences in age and sex. The results for 
the ANCOVA that investigated pre-VlDEO clustering were that 
there was a significant effect of clustering, F(l,38) = 4.60, 
p < .05. Children who had more clustering in their recall 
remembered more words. The three variables in this analysis 
explained 38% of the variation in recall scores. It is 
interesting to note that sex was still significant (as 
discussed in the within-subject follow-up tests for the sex 

by trial interaction on the recall measure), even when age 
and clustering were controlled. However, there were no 
significant age differences in recall. The results of the 
ANCOVA that investigated post-VlDEO recall also had a 
significant effect of clustering, F(l,71) = 10.24, p < .01, 
controlling for differences in age and sex. Again, higher 
clustering was associated with better recall, and the three 
variables explained 17% of the variation in recall scores. 
The results showed no effects of sex or age. Therefore, 
clustering did predict recall, as one would expect. 


Summary of the Results 

The hypothesis that knowledge would increase from the 
pretest to the posttest was supported by both within- and 
between-subject analyses. This increase, however, did not 
occur in all subject groups on all assessments of knowledge. 
All children significantly improved their ability to match 
birds with their correct categories after seeing the 
videotape about birds. However, for the grouping test, the 
change was significant only for boys. That is, girls did not 
significantly improve their ability to place birds into 
meaning-based groups. In addition, older girls did not 
significantly improve the number of birds they could list for 
each category. 

The only knowledge test that did not show improvement 
quantitatively was the facts test. Two different measures 
(i.e., the total number of facts children could generate for 
the birds and the number of birds for which children knew at 
least one fact) did not improve after children saw the 
videotapes. In fact, the post-VlDEO means were slightly 
lower than the pre-VIDEO means. However, the nature of the 


generated facts changed. Whereas few responses for birds 
contained general, category information during the pre-VIDEO 
test, a significantly higher percentage of the facts said 
during the post-VIDEO test contained that type of 
information. This change was evident for both within- and 
between-subject analyses. Because the pictures of the birds 
were not visible for this test, as they had been in the Chi 
and Koeske (1983) study, it was unnecessary to distinguish 
between facts directly related to the picture and facts not 
observable from the picture. 

With respect to the second hypothesis, despite 
significant increases is knowledge, there were no 
corresponding improvements in memory, clustering, or strategy 
use. Although there were significant differences in knowledge 
between older and younger children, there were no age 
differences in recall. Boys did not improve their recall 
after seeing the videotape about birds, even though they 
clearly gained more knowledge about birds than girls. Girls 
also did not improve their recall according to the between- 
subject analysis but did on the within-subject analysis. 
Because there was so much fluctuation (i.e., both 
progressions and regressions) on the memory test, according 
to the individual-subject analysis, there is not a lot of 
evidence to indicate positive change. Only two younger 
females and two older females had recall scores that changed 
more than two points. Clustering and strategy use did not 

improve for any group. Therefore, knowledge improvements did 
not translate into better strategy use or memory, contrary to 
the predictions of current theories of memory development. 
This suggests that improvements in knowledge either are not 
necessary for improvements in memory with age, or that 
knowledge is necessary, but not sufficient, for the 
improvement . 

With respect to the third hypothesis, consistent with 
previous studies which were correlational in nature, each 
knowledge test had a positive correlation with the memory 
test. Older children's knowledge and memory had slightly 
higher correlations than did younger children's. 

The results of the present study are important because 
they raise certain questions that might lead to a clearer 
specification of the relation between knowledge and memory. 
Previous research that credits knowledge as being responsible 
for the major changes in memory with age has been criticized 
for using the term knowledge too globally and ambiguously 
(Saarnio, 1987). In contrast, this study included four 
different assessments of knowledge and thus could provide a 
more refined description of knowledge. Each of the four- 
knowledge tests presented a slightly different picture of the 
relation between knowledge and memory. Thus, all assessments 
of knowledge are not equal, and it is important for future 
studies to include several measures of knowledge. 

The fact that the correlations between knowledge and 

memory increased with age supports the suggestion from 
previous research that categorical information is utilized 
for mnemonic activities to a greater extent by older children 
than younger children. The younger children appeared to be 
more influenced by salient names or perceptual features. For 
example, practically every third grader recalled the birds 
lovebird and titmouse, perhaps because of salient 
associations. Yet, these same children knew nothing about 
those birds, and they tended to group them together with the 
cardinal and bluejay, labeling the group "birds with things 
on top of their heads," a characteristic clearly visible from 
the pictures of those birds. Although very few older 
children knew information about those same birds, they also 
rarely recalled them. 

In conclusion, when the present study looked at the 
relation between knowledge and memory at one point in time, 
it replicated the previously documented correlation between 
knowledge and recall. However, a different picture emerged 
for the group comparisons in the present study that examined 
the effect on recall of constructing new knowledge, a 
comparison that was not possible in previous studies because 
they did not include this manipulation. Improvement in 
knowledge did not lead to increased recall. That new 
associations between birds and their category membership were 
created was apparent from the increases in post-VlDEO 
knowledge test scores. Yet, like many studies showing that 

younger children "have" the available knowledge but do not 
utilize it, a common finding in research on the production 
deficiency, the children in this study apparently did not use 
the new knowledge to enhance their study strategies, 
clustering, or recall. Thus, this study suggested that 
acquiring new knowledge may not guarantee its access. 

Given evidence for correlation but not causality, the 
next question logically becomes "Why?". Interpretations of 
the data will be discussed in the next section. 

Why Correlation But Not Causality? 
There are two main explanations for why increases in 
knowledge did not lead to increases in recall. One has to do 
with the restructuring of knowledge and the other involves 
speed of activation of related information. 

One possible explanation for why the new knowledge was 
not accessed is that although the children acquired the 
associations between the birds and their categories, they did 
not restructure that knowledge into a usable form. Chi 
argues that having categorical associations is not the same 
as having a semantic structure (Chi & Ceci, 1987). Although 
intra-group associations were taught in the videotapes and 
learned by children in the present study, the children may 
not have acquired a class inclusion relation (i.e., that all 
birds in a category simultaneously have certain 
characteristics and are members of the category and, at the 

same time, are part of a larger category, birds). As a 
result, they might not have had access to all the birds 
within a category simultaneously. In this case, children may 
not spontaneously generate category labels and use them to 
generate category members. Therefore, this explanation for 
the results would claim that knowledge may need to be in a 
particular form to become accessible. In other words, 
quality of knowledge, as well as quantity, is important. 
With further exposure to information about birds, children 
might have reorganized their knowledge so that it would have 
become more accessible to them. 

More specifically, knowledge could be structured to be 
more accessible in the following way. Knowledge may 
initially be represented in linear associations, next in 
multiple associations, and finally in hierarchically 
organized associations. If any associations initially were 
simply linear, then activating any member of the pair would 
only activate the other member. Eventually, interconnections 
among items would increase so that knowledge would be 
represented as a network. Take, for example, the analogy of 
a spider web, where each item may be connected to many other 
items, but the network itself is fragile. Activating any 
part of the structure would make accessing any other part of 
the structure more likely, but the whole structure still 
wouLd not be interconnected. At this point, children are 
unlikely to generate a category name and use it as a cue for 

retrieving birds. Eventually, as a greater and greater 
number of associations between birds are established, and 
previous associations become stronger, the form of knowledge 
might change to become a hierarchical structure. The members 
would be perceived as a unit--one of several units of the 
bird kingdom. Activation of any part of the structure would 
simultaneously activate all the other parts; recalling any 
single bird should activate the entire structure and lead to 
the accessing of all birds in that category. Knowledge is 
easily accessed, for one need only retrieve the whole 

Thus, according to this position, memory development 
would be the result of both qualitative and quantitative 
changes in the structure of knowledge. These structural 
changes would make knowledge more accessible. Using the 
above analogy, perhaps knowledge was changed to a form 
similar to the spider web for many children in the present 
study. They were able to list more birds for categories and 
could group a larger number of birds with self-titled 
meaning-based categories. They generated a higher percentage 
of general, categorical facts after watching the videotapes. 
Thus, they had more than single, linear associations. 
However, they may not have been able to retrieve the whole 
structure easily. 

A second possible explanation is that the created 
knowledge was not accessed because the exposure to the 

videotapes did not increase the speed at which the new 
knowledge could be activated, perhaps because of the way the 
information was taught. During the videotapes, associations 
between birds were taught. In an effort to equate the 
teaching of all birds, no more than two birds from the same 
category ever were compared with any other bird in that 
category. Therefore, all the new associations received equal 
attention, and probably had equal strength. 

Perhaps for knowledge to be utilized, some pathways need 
to be traveled more frequently, thus creating stronger routes 
to knowledge rather than simply additional pathways to that 
knowledge. Bjorklund (1987) claims that increases in the 
frequency of occurrence of items probably cause an increase 
in the number and type of features and create more links with 
other items in semantic memory. However, the results of this 
study suggest that simply creating more links (by teaching 
facts about birds) does not appear to be sufficient, and 
although the number of links from categories to birds or 
birds to categories increased in this study, that too was not 
sufficient for improved memory. Perhaps frequent exposure to 
items is necessary so the links between items become well- 
practiced, and it is only after the information can be 
activated more readily that knowledge is utilized. More 
specifically, repeated exposure to swans, geese, and ducks in 
the context of water may result in water and the names of 

these birds immediately becoming activated when any single 
bird is recalled or encountered. 

The correct answer to "What is memory the development 
of?" might be "knowledge, ease of access, and strategies, in 
that order of acquisition." This answer would suggest that 
knowledge and ease of accessing that knowledge are precursors 
for strategy development, and that increased strategy usage, 
particularly strategies that tie the material to be learned 
with prior knowledge, is what increases memory performance. 
More specifically, memory development might proceed as 
follows: First, perhaps some knowledge of the area is 
acquired. This foundation of knowledge might be necessary as 
a first step. In this study, children appeared to acquire 
categorical knowledge mainly about those birds for which they 
had previous information. Evidence is that the number of 
birds for which they generated facts did not change but the 
type of facts they generated changed significantly (i.e., 
referred to more general, categorical information). Second, 
repeated experience with the knowledge may strengthen 
semantic grouping connections and weaken other facts , such as 
perceptually-based facts. The outcome is a categorical 
organization with knowledge structured in a more usable form 
and/or with faster speed of activation of related 
information. Third, easier access or faster activation means 
that more sophisticated study strategies can be utilized, 
because semantic relations are easily accessed. With few 

exceptions, the body of research in cognitive psychology 
confirms the superiority of performance on free-recall tasks 
when the information is encoded semantically . 

Either of the above explanations (i.e., structural or 
speed changes), or perhaps some process unexplored here, 
taken as intermediate steps between knowledge and memory, 
would explain why having the knowledge is not sufficient for 
improvements in strategy use or recall. Early research 
generated by the hypothesis that younger children had a 
production deficiency claimed that younger children had the 
relevant categorical knowledge that could help them recall 
but tended not to use it. The claim here is that one reason 
for a production deficiency is that knowledge that cannot be 
accessed readily due to its primitive structure or its slow 
speed of activation will not be utilized. These accounts 
also explain why preschool children only use strategies when 
involved with very familiar material. 

In other work on strategies (e.g., Gobbo & Chi, 1986; 
Ornstein & Naus, as cited by Zembar & Naus, 1985a), those who 
already can access knowledge readily (experts) are compared 
with those who cannot (novices). Studies by Bjorklund and 
others (Bjorklund & Thompson, 19 8 3; Buchanan & Bjorklund, 
1988) compare very familiar knowledge (typical items) with 
moderately familiar knowledge (atypical items). Studies by 
Lindberg (1980) and Zembar and Naus (1985b) compare knowledge 
that is very familiar (or very salient) for one group with 

knowledge that is unfamiliar for that group. All of these 
studies find increased use of strategies associated with the 
former type of knowledge in the contrasted pair. However, it 
can be argued that it is not simply a difference in knowledge 
per se, but the likely differences in either the structure of 
knowledge, the speed of activation of related knowledge, 
both, or a factor unexplored here, that actually contributed 
to the observed increased use of strategies. 

In addition, it should be noted that Bjorklund's 
comparisons of typical and atypical items contrast two types 
of knowledge that both, for the most part, are at the upper 
end of the continuum. Most people do not name watermelon as 
the first response when asked to list pieces of fruit, but 
readily would agree that it is a member of that category, and 
they might name it readily during certain months of the year. 
Therefore, although subjects' knowledge differs with regard 
to the structure of categories or the speed of activation of 
their atypical members, minimal training would be necessary 
to facilitate the subjects' ability to access it. That would 
not be true in the present study, which examines moderate 
levels of knowledge. 

It might be argued that including a larger number of 
subjects or identifying and removing artifacts of measurement 
might reveal a significant change in recall. If the lack of 
improvement in recall were due only to too few subjects, then 
the knowledge tests should have been influenced as well, in 

fact, a greater number of subjects took the memory test twice 
than the knowledge tests twice, so the statistical test for 
changes in memory actually had more power. Furthermore, the 
individual-subject data analysis revealed entirely different 
patterns of results for the knowledge and memory tests . 
Whereas the knowledge tests clearly showed that a majority of 
the subjects improved (especially older children, almost all 
of whom improved somewhat), the recall test showed that 
almost equal numbers of children had scores that increased, 
decreased, or stayed the same. Furthermore, the majority of 
children's pretest and posttest recall scores were within one 
point of each other. Finally, the lack of improvement in the 
recall of males was not due to a ceiling effect. They 
recalled only an average of 9.86 of the 20 possible words on 
the pretest. Therefore, they had adequate room for 
improvement . 

In an effort to generalize the results with certainty to 
those of correlational studies, a design was used in which no 
child took all the tests. However, that prevented the 
within-subject measurements of both knowledge and memory for 
the same children. The fact that the three conditions did 
not differ on any test suggests that children can take all 
the tests in future research without introducing practice 
effects or sacrificing the generality of the results. 

Other Issues and Future Research 

In this first experimental (not simply correlational) 
investigation of the relation between knowledge and memory, 
care was taken not to present knowledge in such a way that 
any changes in memory would appear to be trivial. A main 
consideration for designing the instruction about birds was 
that it was desirable to focus on two changes in specific 
aspects of knowledge identified as important for memory in 
previous research. One was creating a larger number of 
intra-group associations, which was the major characteristic 
that separated the well-known and less-familiar dinosaurs 
known by a boy in the study by Chi & Koeske (1983). The 
other was changing children's focus upon physical 
characteristics to a focus on meaning-based characteristics, 
labeled explicit and implicit propositions by Gobbo & Chi 
(1986), and found to distinguish experts from novices. This 
previous research suggested that these changes in knowledge 
would be sufficient for changes in memory. The results of 
this study indicate that these knowledge differences alone 
may not be the cause of improvements in memory. Thus, future 
research should attempt to specify the nature of the relation 
between knowledge and memory more clearly. 

In particular, future research should investigate the 
possibilities that restructuring of knowledge or changes in 
the speed of activation are intermediate steps to improvement 
in memory. The structure of knowledge purposefully was not 

taught directly. That is, the videotapes did not present a 
category name and then list all of the birds in that 
category. Children neither saw all the birds belonging to a 
category at once nor were given the labels for all the 
different categories at one time. Therefore, any changes in 
memory would not be trivial. As in real life, children had 
to do some construction of any hierarchical knowledge about 
birds and categories. The fact that increased knowledge did 
not bring increased recall suggests that the necessity to 
construct the categorical knowledge was too effortful for 
children to do for birds about which they had little prior 
information or experience. It would be interesting to 
determine whether children would learn new birds more readily 
if they were provided with the hierarchy of categories from 
the outset. Giving children that structure before they saw 
the videotapes might facilitate their acquisition of a 
knowledge structure, even if the birds were taught randomly, 
as they were in this study. 

One important aspect of knowledge acquisition may be 
that members of a category be encountered in the same context 
or at about the same time. To determine whether proximity of 
learning is an important cue for restructuring knowledge, the 
lessons about birds could be rearranged for one group of 
children to see if that facilitated their later use of that 
knowledge for recall. The lessons about all the birds from 
one category would appear consecutively, instead of being 

interspersed with birds from other categories. In the real 
world, learning generally occurs either in the same physical 
context or within a time context. For example, children 
encounter swans, ducks, and geese at the lake (physical 
context), or children may hear a whip-poor-will, a chuck- 
will ' s-widow, or an owl at about the same time on different 
nights (a time context). The children still would need to do 
some construction of a knowledge structure, because the birds 
would not be explicitly identified as belonging to a 
category, and the nature of that category would not be 
explained. Research also could examine the argument that 
speed of access of knowledge is what is important. Perhaps 
training children on half the number of birds, thus spending 
twice the amount of time on each, would facilitate recall. 

Another approach for future research is to use other 
tasks. For example, a task similar to the clue game (the 
child and experimenter take turns giving properties and 
identifying the "creature") utilized by Chi and Koeske (1983) 
might be attempted with a small number of children both 
before and after training. Assessment of the structure of 
children's knowledge might include a traditional Piagetian 
class-inclusion task. Then the probabilities of trained 
versus untrained birds being represented hierarchically could 
be compared. 

Because an important part of this initial study was to 
look at children's spontaneous strategy use, it was decided 

to record spontaneous overt strategies rather than to elicit 
particular strategies from children. Like other studies that 
infer strategy use from overt behaviors, precision of 
measurement often is sacrificed. For example, because very 
few children rehearsed aloud, the definition of rehearsal 
also included obvious lip movement, obvious head-bobbing, or 
any combination of the two. Therefore, some children could 
have been rehearsing covertly, but were not classified as 
such because they produced no observable indicators. 
Spontaneous strategy use actually was quite low, so the next 
step would be to instruct children to use strategies. With 
this design, increases in knowledge may lead to increased 
ability to profit from this instruction. 

One example of elicited strategies from children would 
be having children sort the birds for recall. A comparison 
of the well-trained versus untrained birds would be made. 
Would children be more likely to group the well-trained birds 
by meaning, and consequently to recall those particular birds 

Another series of studies could investigate whether 
changes in the speed of activation alone were necessary for 
improved strategy use and memory. Children would receive 
practice identifying the appropriate category for half of the 
items on a list of birds. The pretest and posttest memory 
test would include a measurement of the style and content of 
the children's rehearsal (which they would be asked to 

perform aloud). Comparisons would be made of the trained 
versus untrained items. Would children be more likely to 
include the trained than the untrained items in their 
rehearsal sets? Would their rehearsal become more active and 
contain a greater number of items from the same category when 
they could access the items and category information more 

The results of the present study challenge current views 
of the relation between knowledge and memory development. 
The question of "What is memory the development of?" is far 
from answered, and it is time to rethink the old answers, 
redefine possible mechanisms for change, clarify old 
theories, or invent and test new ones. In particular, it is 
crucial that researchers attempt to a) define and measure 
knowledge with multiple tests and b) conduct more 
experimental tests in which new knowledge is created. Both 
are virtues of the present study. 



Birds of Prey 




Birds People Eat 




Talking Birds 


Birds of Prey 




Birds People Eat 




Talking Birds 

B irds Awake at Night 

Birds that Live by Water 
















Birds Awake at Night 
chuck-will ' s-widow 

Birds that Live by Water 





bluej ay 

7 9 


Day 1 (17 minutes) 

General Introduction 

Introduction to Water Birds 

Trumpeter Swan 

Introduction to Songbirds 

Tufted Titmouse 

Ring-Billed Gull 

Carolina Chickadee 

Introduction to Birds People Eat 

Canada Goose 


Wild Turkey 

Killdeer Plover 


Day 2 (12 1/2 minutes) 


Sanderling Sandpiper 

Chipping Sparrow 

Introduction to Birds Awake 

at Night 
Great-Horned Owl 
Eastern Bluebird 

Day 3 

Royal Tern 

Bluej ay 

Great Blue Heron 

American Goldfinch 

American Oystercatcher 

Chuck-will ' s-widow 


Day 4 

Bantam Rooster (chicken) 


Introduction to Birds of 

Swallow-tailed Kite 
Ruffed Grouse 
Bald Eagle 
Ring-necked Pheasant 

Day 5 

Sharp-Shinned Hawk 

Bobwhite Quail 

Red-tailed Hawk (Buzzard) 




Turkey Vulture 



Royal Tern 

Like the sandpiper and the plover, a tern lives near the 
beach. In fact, it only lives near salt water, never near 
lakes or rivers like some other water birds. 

Unlike the sandpipers, terns spend most of the daylight 
hours in the air flying, and they're clumsy on land. You 
won't find terns running up and down the beach the way 
sandpipers do. Tern's long tails help them to make quick 
turns to the right or left when they are flying. 

The Royal Tern is a large tern with a heavy orange-red 
bill, black cap, pale gray back and wings, white forehead and 
black crest. Their tail has a slight fork (or V) in it. The 
Royal Tern's wings are long and narrow, like the plover's 
wings are. 

When terns search for food, they fly over the water with 
their bill pointed downward. Then they dive into the water 
from the air to catch fish. Royal Terns eat only fish. 

There's usually not much material for a nest at the 
seashore. Few plants can grow in loose sand that's 
constantly stirred and shifted by wind. So, many kinds of 
seashore-dwelling birds (such as the Royal Tern) either lay 
their eggs right on the sand or else scoop out a slight hole 
(like the sandpiper does) and lay their eggs in that. The 
eggs of many seashore birds are splotched and streaked with 
color that makes them look like a bunch of pebbles. Thus, 
although the eggs are right out in the open, they're well 
hidden by blending in with the beach. So, like plovers, 
terns have a clever way to protect their young! 

American Goldfinch 

Unlike the noisy, screaming, poor songs of the bluejay, 
the goldfinch sings a bright song "per-chick-o-ree. " As it 
flies, it also sings a song in time with the beat of its 
wings. That song sounds like "potato-chips." 

The male and female bluebirds and bluejays are similar. 
Not so for the American Goldfinch. In fact, the American 
Goldfinch even looks different in the summer and winter. 

In the spring and summer, the male is bright yellow with 
white edges on black wings and tail and a black forehead. In 
the winter the male looks more like the female: dull yellow, 
brown with wing bars and no black on their heads. 
Goldfinches are much smaller than bluebirds or bluejays. 

You can recognize a Goldfinch when it's flying, because 

it flies like a roller coaster up and down and up and 




The goldfinch's main food is seeds. It especially likes 
tiny seeds, so it has a little pointed bill to help it get 
weed seeds, small grain, and some wild fruit. Because weed 
seeds aren't available until late summer, baby Goldfinches 
hatch much later than other birds like the bluebird and 
bluejay. Goldfinches wait to lay eggs so they will have lots 
of food for their babies. 

The goldfinch is often called the "wild canary", because 
of its yellow color and clear song. 


The nighthawk 's name tells you one time of day that you 
will find it flying. Can you guess when that is? 

Yes, like the chuck-will' s-widow and the whip-poor-will, 
nighthawks are birds that can be heard during the night. It 
repeats a buzzy "beans, beans, beans." The nighthawk is 
different from the chuck-will' s-widow and the whip-poor-will 
though, because it often flies in the sunlight, too. 

The nighthawk is not a hawk. It's actually a close 
relative of the whip-poor-will and is the same size, too. 
You can tell the nighthawk and whip-poor-will apart, because 
the nighthawk is darker and has a longer tail that has a fork 
(or V) at the end. It has a white patch on its wings, too. 
It also doesn't spend most of its time on the ground like the 
whip-poor-will and chuck-will ' s-widow. Instead, it is 
constantly in the air, flying in a zig-zag pattern, circling, 
diving, and banking. 

It catches flying insects on its wing like the whip- 
poor-will does. It also flies with its short-billed mouth 
wide open. In one single day, one nighthawk ate over 500 
mosquitoes and another one ate 2175 flying ants! The next 
time you're out at night getting bitten by mosquitoes, try to 
find a nighthawk to get rid of those pests! 




my nan 










chuck-will ' s-widow 



blue j ay 
































1 = Birds of Prey 

2 = Birds People Eat 

3 = Talking Birds 

4 = Birds Awake at Night 

5 = Birds that Live by Water 

6 = Songbirds 













chuck-will ' s-widow 









4 or 6 










































blue j ay 





2 or 5 








4 or 6 












Acceptable Answers: hawk, vulture, eagle, kestrel, 
osprey, kite, buzzard, snakebird, gull, 
oystercatcher , heron, tern, owl 

Unacceptable Answers: nighthawk, titmouse, guail, 
bluejay, sandpiper, duck 


Acceptable Answers: goose, pheasant, chicken, quail, 

turkey, grouse, dove, duck 
Unacceptable Answers: sparrow, titmouse, wren, any other 



Acceptable Answers: cockatoo, monk, mynah, lory, parrot, 

lovebird, parakeet, macaw 
Unacceptable Answers: whip-poor-will, chuck-will ' s- 

widow, chickadee, mockingbird, cardinal, canary 


Acceptable Answers: chuck-will ' s-widow, whip-poor-will, 

mockingbird, nightingale, owl, nighthawk 
Unacceptable Answers: starling, chickadee, osprey, bat 


Acceptable Answers: plover, oystercatcher, goose, heron, 
tern, swan, snakebird, gull, sandpiper, stork, 
crane, coot, flamingo, egret, duck, pelican 

Unacceptable Answers: turkey, quail, swallow 


Acceptable Answers: bluebird, blackbird, cardinal, 
titmouse, chickadee, mockingbird, goldfinch, 
sparrow, bluejay, nightingale, starling, swallow, 
robin, canary 

Unacceptable Answers: whip-poor-will, chuck-will ' s- 

widow, lovebird, parrot, quail, crow, owl, lory, 
dove, hummingbird, parakeet, killdeer, pigeon 





ARC = R - E (R) 

max R - E (R) 


R ■ total number of observed category repetitions (i.e., 
the number of times a category item follows an item 
from the same category), 

max R = maximum possible number of category 


E (R) = expected (chance) number of category 
repetitions . 

It should be noted that 

max R = N - k, 

where N = total number of items recalled, 

and k = number of categories represented in the recall 

And, (from Bousefield & Bousefield, 1966, as cited by 
Roenker, Thompson, & Brown, 1971) 

E (R) = Sigma n^ 2 - 1 



n^ 2 = number of items recalled from category i, and N is 
as before. (p. 46) 



Involvement With the Task 

* leaned forward 

* stood up 


* lips moving 

* bobbed head up and down (at least two times 

consecutively ) 

* said the names of birds aloud 

Involvement With the Cards 

pointed at cards (no contact made) 

<5 * 5 - 10 *>10 

touched the cards (contact made but the positions of 

cards unchanged) 

<5 * 5 - 10 *>10 

moved the cards (contact made and positions of cards 

changed ) 

*<5 *5-10 *>10 


* looked up > 1 second in duration 

* looked to the side > 1 second in duration 

* closed eyes > 1 second in duration 

* covered the names of birds with hand 

Note: Starred items were considered "strategic." Children 
received one point for each of the four strategy 
categories that had at least one starred item checked or 
circled. Then the points were summed to obtain a 
composite strategy score (maximum =4). 



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Darlene DeMarie Dreblow was born in New York, but she 
never considered herself a "New Yorker." She earned a BA 
from Marietta College in 1974, an MEd from Ohio University 
in 1978, an MS from the University of Florida in 1985, and 
will be receiving her PhD from the University of Florida in 
1988, but she currently is not a student. She loved teaching 
elementary school children (looking forward to every day when 
she taught first grade, second grade, and learning 
disabilities for seven years) but left to attend graduate 
school anyway. After striving to achieve a "mellow" 
existence for many years, Darlene broke the life-events 
record during graduate school. 

Darlene hates the cold but currently lives in 
Cambridge, Ohio. She lives on a 98-acre farm, but she is not 
a "farmer." She teaches at a small, liberal arts college 
(Muskingum College in New Concord, Ohio), but she plans to 
remain active in research. She has a family but rarely has 
time to be a "mother" or a "wife." 

These ironies in life have been inevitable. Hopefully, 
they have strengthened Darlene for her pursuit for harmonious 
relations among self, soul, and situation in the future. 


o D inion C ?? tifY ^ that J have read this stud Y and that in my 
opinion it conforms to acceptable standards of scholarlv 

Patricia H. Miller, Chairperson 
Professor of Psychology 

-i^ 1 ce ftify that I have read this study and that in mv 
SeSen^M cont ™* to acceptable standards of scholar^ 

Son" n^i-H 111 ^ adequate, in soope and quality, as 
a Dissertation for the degree of Doctor of Philosophy. 

Professor of Psychology 

Ira Fischler 

Professor of Psychology 

Richard Griggs / / 
Professor of Psychology 

I certify that I have read this study and that in my 
opinion it conforms to acceptable standards of scholarly 
presentation and is fully adequate, in scope and quality, as 
a dissertation for the degree of Doctor of Philosophy. 

ft. a ™~-4J± Qvp i a a.£L 

J&Vnes Algina Y 
P^Jafessor of Foundations of 

I certify that I have read this study and that in my 
opinion it conforms to acceptable standards of scholarly 
presentation and is fully adequate, in scope and quality, as 
a dissertation for the degree of Doctor of Philosophy. 

Robin West 

Assistant Professor of Psychology 

This dissertation was submitted to the Graduate Faculty 
of the Department of Psychology in the College of Liberal 
Arts and Sciences and to the Graduate School and was accepted 
as partial fulfillment of the requirements for the degree of 
Doctor of Philosophy. 

December, 1988 Dean, Graduate School